| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 1 | | adverbTags | | 0 | "It stepped aside [aside]" |
| | dialogueSentences | 8 | | tagDensity | 0.125 | | leniency | 0.25 | | rawRatio | 1 | | effectiveRatio | 0.25 | |
| 90.96% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1659 | | totalAiIsmAdverbs | 3 | | found | | 0 | | | 1 | | adverb | "reluctantly" | | count | 1 |
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| | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 69.86% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1659 | | totalAiIsms | 10 | | found | | | highlights | | 0 | "weight" | | 1 | "rhythmic" | | 2 | "shimmered" | | 3 | "could feel" | | 4 | "glint" | | 5 | "database" | | 6 | "churned" | | 7 | "pulsed" | | 8 | "scanning" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 128 | | matches | (empty) | |
| 53.57% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 7 | | narrationSentences | 128 | | filterMatches | | | hedgeMatches | | 0 | "seemed to" | | 1 | "tried to" | | 2 | "begin to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 135 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1637 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 8 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 41 | | wordCount | 1532 | | uniqueNames | 14 | | maxNameDensity | 0.91 | | worstName | "Quinn" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Quinn" | | discoveredNames | | Camden | 2 | | Harlow | 1 | | Quinn | 14 | | Chalk | 1 | | Farm | 1 | | Road | 1 | | Herrera | 7 | | Thames | 3 | | Morris | 5 | | Underground | 1 | | Tube | 1 | | Tomás | 2 | | Metropolitan | 1 | | Police | 1 |
| | persons | | 0 | "Camden" | | 1 | "Harlow" | | 2 | "Quinn" | | 3 | "Herrera" | | 4 | "Morris" | | 5 | "Tomás" |
| | places | | 0 | "Chalk" | | 1 | "Farm" | | 2 | "Road" | | 3 | "Thames" |
| | globalScore | 1 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 89 | | glossingSentenceCount | 11 | | matches | | 0 | "quite explain" | | 1 | "looked like an abandoned loading dock beh" | | 2 | "looked like it led to some kind of servic" | | 3 | "looked like they'd been made by something" | | 4 | "felt like moss" | | 5 | "looked like an old maintenance tunnel for" | | 6 | "light that seemed to bend around corners" | | 7 | "something like ozone" | | 8 | "cloak that seemed to absorb light" | | 9 | "looked like it had been made by a knife" | | 10 | "titles that seemed to change when she looked away" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.611 | | wordCount | 1637 | | matches | | 0 | "Not specifically, but this" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 135 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 52 | | mean | 31.48 | | std | 22.72 | | cv | 0.722 | | sampleLengths | | 0 | 71 | | 1 | 2 | | 2 | 27 | | 3 | 54 | | 4 | 61 | | 5 | 50 | | 6 | 48 | | 7 | 38 | | 8 | 3 | | 9 | 50 | | 10 | 9 | | 11 | 33 | | 12 | 53 | | 13 | 11 | | 14 | 49 | | 15 | 17 | | 16 | 3 | | 17 | 78 | | 18 | 24 | | 19 | 45 | | 20 | 98 | | 21 | 17 | | 22 | 34 | | 23 | 13 | | 24 | 41 | | 25 | 33 | | 26 | 23 | | 27 | 43 | | 28 | 1 | | 29 | 23 | | 30 | 2 | | 31 | 6 | | 32 | 16 | | 33 | 13 | | 34 | 45 | | 35 | 46 | | 36 | 48 | | 37 | 67 | | 38 | 17 | | 39 | 25 | | 40 | 33 | | 41 | 4 | | 42 | 42 | | 43 | 4 | | 44 | 18 | | 45 | 42 | | 46 | 9 | | 47 | 62 | | 48 | 54 | | 49 | 26 |
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| 91.56% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 128 | | matches | | 0 | "was gone" | | 1 | "been made" | | 2 | "been touched" | | 3 | "been made" | | 4 | "been seemed" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 284 | | matches | | 0 | "was standing" | | 1 | "was getting" | | 2 | "was speaking" | | 3 | "was heading" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 15 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 135 | | ratio | 0.081 | | matches | | 0 | "Quinn counted as she descended—ten rungs, twenty, thirty—until her boots finally hit solid ground." | | 1 | "And music—something rhythmic and strange, played on instruments she couldn't identify." | | 2 | "Hundreds of people—if they were all people—moved through the narrow aisles, examining goods, exchanging currency that glinted strangely, speaking in languages Quinn didn't recognize." | | 3 | "She could smell it—incense and copper and something like ozone." | | 4 | "She could see his face now—olive skin, curly dark hair, the glint of something gold around his neck." | | 5 | "A hand emerged from the cloak's folds—too long, too many joints—and extended palm up." | | 6 | "The scar on his left forearm caught the lantern light—a long, ugly thing that looked like it had been made by a knife." | | 7 | "And now this—a hidden world beneath the city, a market that dealt in things she couldn't name." | | 8 | "He'd gotten whatever he came for—a small package wrapped in cloth that he tucked into his jacket—and was heading for another exit on the far side of the station." | | 9 | "Inside was a fragment of bone—recovered from one of the Thames victims, kept on her person because something about it felt important, felt connected." | | 10 | "The crowd parted around her reluctantly, bodies that felt wrong when they brushed against her—too cold, too warm, too angular beneath their clothing." |
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| 97.81% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1553 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 66 | | adverbRatio | 0.04249839021249195 | | lyAdverbCount | 15 | | lyAdverbRatio | 0.009658725048293626 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 135 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 135 | | mean | 12.13 | | std | 8.96 | | cv | 0.739 | | sampleLengths | | 0 | 19 | | 1 | 27 | | 2 | 25 | | 3 | 2 | | 4 | 12 | | 5 | 5 | | 6 | 10 | | 7 | 32 | | 8 | 22 | | 9 | 2 | | 10 | 7 | | 11 | 2 | | 12 | 2 | | 13 | 19 | | 14 | 29 | | 15 | 11 | | 16 | 19 | | 17 | 13 | | 18 | 7 | | 19 | 7 | | 20 | 9 | | 21 | 17 | | 22 | 15 | | 23 | 15 | | 24 | 3 | | 25 | 20 | | 26 | 3 | | 27 | 9 | | 28 | 41 | | 29 | 4 | | 30 | 5 | | 31 | 8 | | 32 | 2 | | 33 | 2 | | 34 | 10 | | 35 | 11 | | 36 | 6 | | 37 | 13 | | 38 | 34 | | 39 | 11 | | 40 | 23 | | 41 | 9 | | 42 | 13 | | 43 | 2 | | 44 | 2 | | 45 | 13 | | 46 | 2 | | 47 | 2 | | 48 | 3 | | 49 | 12 |
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| 62.96% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.4222222222222222 | | totalSentences | 135 | | uniqueOpeners | 57 | |
| 28.74% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 116 | | matches | | 0 | "Just the distant orange glow" |
| | ratio | 0.009 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 116 | | matches | | 0 | "She knew he wouldn't stop." | | 1 | "They never did when they" | | 2 | "She hit the gap between" | | 3 | "She blinked it away and" | | 4 | "She dropped down hard, felt" | | 5 | "She pulled out her phone," | | 6 | "She should call for backup," | | 7 | "She'd waited for backup while" | | 8 | "She could hear water rushing" | | 9 | "Her hand moved to her" | | 10 | "She climbed down." | | 11 | "She was standing in what" | | 12 | "She followed the sounds, taking" | | 13 | "She could smell it—incense and" | | 14 | "She could feel the vibration" | | 15 | "He'd pushed back his hood." | | 16 | "She could see his face" | | 17 | "He was moving fast but" | | 18 | "She could draw it." | | 19 | "She could announce herself, demand" |
| | ratio | 0.276 | |
| 72.07% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 90 | | totalSentences | 116 | | matches | | 0 | "Detective Harlow Quinn's boots slammed" | | 1 | "The words tore from her" | | 2 | "She knew he wouldn't stop." | | 3 | "They never did when they" | | 4 | "Quinn pushed herself faster, ignoring" | | 5 | "The worn leather of her" | | 6 | "That was the name in" | | 7 | "She hit the gap between" | | 8 | "The alley was narrow, barely" | | 9 | "Water cascaded down from somewhere" | | 10 | "She blinked it away and" | | 11 | "Quinn grabbed the metal links" | | 12 | "She dropped down hard, felt" | | 13 | "The alley opened onto what" | | 14 | "Herrera was gone." | | 15 | "Quinn stopped, chest heaving, turning" | | 16 | "The loading dock offered three" | | 17 | "The grate was askew." | | 18 | "Someone had moved it recently." | | 19 | "She pulled out her phone," |
| | ratio | 0.776 | |
| 43.10% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 116 | | matches | | 0 | "By the time she'd caught" |
| | ratio | 0.009 | |
| 58.82% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 68 | | technicalSentenceCount | 8 | | matches | | 0 | "Quinn pushed herself faster, ignoring the burn in her lungs, the ache in her forty-one-year-old knees that reminded her she wasn't the young constable who'd onc…" | | 1 | "Lost his medical license under circumstances that didn't add up no matter how many times she read the reports." | | 2 | "And now connected to at least three bodies that had turned up in the Thames over the past month, each one bearing wounds that the coroner couldn't quite explain…" | | 3 | "She followed the sounds, taking the left fork, then right, then left again, until she emerged onto a platform overlooking something that made her stop dead." | | 4 | "Hundreds of people—if they were all people—moved through the narrow aisles, examining goods, exchanging currency that glinted strangely, speaking in languages Q…" | | 5 | "A former paramedic who'd lost his license for treating patients that weren't in any medical database." | | 6 | "The crowd parted around her reluctantly, bodies that felt wrong when they brushed against her—too cold, too warm, too angular beneath their clothing." | | 7 | "Eyes watched her from stalls and corners and high places, eyes that knew she didn't belong here." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |